code: def spline_slope_constraint(s, dtype=tf.float32):
      """Maps `s` to all positive with `s[..., 0] == s[..., -1] == 1`."""
      # Slice off a position since this is nknots - 2 vs nknots - 1 for bin sizes.
      min_slope = 1e-2
      return tf.math.softplus(tf.cast(s[..., :-1], dtype)) + min_slope
  
imports: import collections
  import inspect
  from absl import logging
  import hypothesis.strategies
  import tensorflow.compat.v2
  from tensorflow_probability.python import bijectors
  from tensorflow_probability.python.distributions import lkj
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 9 for calling a global function with example usage: spline_slope_constraint(s, dtype) and returns: unknown